Technical Delivery Manager - Agentic AI Engineering; Manager

Location:

Anywhere in Country

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We are seeking a seasoned Technical Delivery Manager to drive the day-to-day execution of the engineering teams building EY’s Agentic AI platform. This role owns delivery cadence across multiple development programs: running the Scrum process and its ceremonies, keeping work flowing, and holding engineers accountable for what they committed to and when. You will be the person who knows, at any moment, what is genuinely in flight, what is genuinely blocked, and what is quietly slipping.

This is deliberately not a facilitation-only role; you must understand what is actually being built (Kubernetes and GPU infrastructure, CI/CD/CV pipelines, model serving and routing, agent orchestration, data and state layers) well enough to interrogate an estimate, tell a real dependency from a convenient one, and challenge scope and sizing with evidence.

The role is ideal for an engineer-turned-delivery-lead who is credible with senior engineers because they have done the work themselves, who is comfortable being the person who asks the uncomfortable question in stand-up, and who measures success in working capability shipped against committed dates rather than in ceremonies run or boards kept tidy.

• Own the delivery cadence: run daily stand-ups, sprint planning, backlog refinement, sprint reviews, and retrospectives across the engineering teams, keeping every ceremony short, decision-focused, and genuinely useful to the engineers in the room.
• Drive progress against commitments: track every in-flight item through to completion, surface slippage on the day it happens rather than at sprint end, and ensure blocked work is actually unblocked rather than quietly rescheduled.
• Hold engineers accountable to deliverables and timelines: agree explicit definitions of done and dated commitments, follow them up personally, and elevate early and credibly when delivery is at risk.
• Interrogate estimates and challenge padding: apply your own technical judgement to test sizing, decomposition, and complexity claims, separate genuine engineering risk from conservative buffering, and hold estimates to what the work actually requires.
• Break down ambiguous work: translate architecture intent, phase gates, and platform capability requirements into properly sized, independently deliverable stories with unambiguous acceptance criteria.
• Own sprint and release planning across the phased platform build: sequence work so each phase puts usable capability into engineering teams’ hands, and defend entry and exit gates rather than letting them soften under schedule pressure.
• Manage cross-discipline dependencies: coordinate hand-offs between platform and infrastructure, runtime and observability, data and state, trust infrastructure, security, and the AFE delivery cells.
• Own delivery risk and issue management: maintain a live view of risks, dependencies, and the critical path, drive mitigation to closure, and make trade-offs explicit to leadership while there is still time to act on them.
• Report delivery status with evidence: velocity, throughput, cycle time, flow efficiency, escaped defects, and burn against phase gates, reported honestly and without softening, including when the news is bad.
• Protect the team’s focus: absorb interruptions, scope injection, and competing stakeholder demands so engineers get uninterrupted delivery time.
• Partner with engineering leads and architects: on sequencing, staffing, and technical direction, with a clear…